42711735517a3f8f53ca68b5a0776a13a6f6197c
examples/alphafold2.md
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7 | 7 | - [Using the default run_alphafold.sh wrapper](#using-the-default-run_alphafoldsh-wrapper) |
8 | 8 | - [Creating your own run_alphafold script](#creating-your-own-run_alphafold-script) |
9 | 9 | - [Running the python script run_alphafold.py directly](#running-the-python-script-run_alphafoldpy-directly) |
10 | - - [GPU Memory:](#gpu-memory) |
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11 | - - [pTM scores:](#ptm-scores) |
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12 | - - [Examples:](#examples) |
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10 | + - [GPU Memory](#gpu-memory) |
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11 | + - [pTM scores](#ptm-scores) |
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12 | + - [Examples](#examples) |
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13 | 13 | - [Web portal](#web-portal) |
14 | 14 | - [Known issues](#known-issues) |
15 | 15 | |
... | ... | @@ -102,18 +102,17 @@ You can use our run_alphafold script template here to create your own run script |
102 | 102 | ### Running the python script run_alphafold.py directly |
103 | 103 | run_alphafold.sh is a convenience wrapper script that shortens the required command arguments to run_alphafold.py. The run_alphafold.py script is also available which requires all parameters to be set explicitly, but provides greater flexibility. Pass --helpshort or --helpfull to see help on flags. |
104 | 104 | |
105 | -### GPU Memory: |
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105 | +### GPU Memory |
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106 | 106 | Memory is going to be an issue with larger protein sizes. The original publication suggests some things to try: |
107 | 107 | |
108 | 108 | "Inferencing large proteins can easily exceed the memory of a single GPU. For a V100 with 16 GB of memory, we can predict the structure of proteins up to ~1,300 residues without ensembling and the 256- and 384-residue inference times are using a single GPU’s memory. " |
109 | 109 | |
110 | 110 | "The memory usage is approximately quadratic in the number of residues, so a 2,500 residue protein involves using unified memory so that we can greatly exceed the memory of a single V100. In our cloud setup, a single V100 is used for computation on a 2,500 residue protein but we requested four GPUs to have sufficient memory." |
111 | 111 | |
112 | -### pTM scores: |
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112 | +### pTM scores |
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113 | 113 | The pTM scores are not calculated using the default model. To get pTM scored models you need to change the model names in the input. We have provided a template wrapper script (https://sbgrid.org//wiki/examples/alphafold2) which you can change to your requirements. To get pTM scores you will need to change the model_name line to "model_1_ptm,model_2_ptm" etc. |
114 | 114 | |
115 | -### Examples: |
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116 | - |
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115 | +### Examples |
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117 | 116 | We include reference sequences from CASP14 in the installation. |
118 | 117 | This command should run successfully: |
119 | 118 |